p53 acts in a complex tumor suppressor network that mediates cellular responses to stress. Thus, p53 is[unreadable] activated in response to diverse cellular insults, including mitogenic oncogenes, hypoxia, oxidative stress,[unreadable] and DNA damage. Once activated, p53 can trigger a variety of anti-proliferative programs, including[unreadable] apoptosis and cellular senescence, by targeting multiple components of each program's effector[unreadable] machineries. Since many of the chemotherapeutic agents currently used to treat cancer directly or indirectly[unreadable] damage DNA, they often rely on the integrity of the p53 pathway to elicit their anti-tumor effects. As a[unreadable] consequence, drug resistance can arise as a byproduct of tumor evolution. This project is interested in how[unreadable] p53 modulates the action of conventional and targeted drugs, and the implications of disrupting the p53[unreadable] network at different points from tumor evolution to drug resistance. To study these processes, we use the[unreadable] E-mu-myc transgenic model of B-cell lymphoma as a tractable yet physiological test system. Over the last[unreadable] funding period, we developed methods to rapidly produce lymphomas with complex genotypes, and then[unreadable] study the impact of these lesions on tumor cell responses to therapy using approaches that parallel clinical[unreadable] trials. Using this system, we identified a number of biological (apoptosis, senescence, translational control)[unreadable] and genetic (p53, ARF, INK4a/ARF, Bcl-2, Akt, elF4E) determinants of drug action. In the current proposal,[unreadable] we will continue to study components of the p53 network that influence apoptosis and senescence for their[unreadable] impact on chemosensitivity, and will examine how survival signaling through the PI3kinase/Akt network[unreadable] affects p53 action to promote chemoresistance. However, we also will initiate efforts to explore the utility of[unreadable] the E-mu-myc system to study new drugs, in particular, by testing strategies to reverse chemoresistance in[unreadable] vivo. Furthermore, we will exploit the unique features of the E-mu-myc model to conduct high throughput[unreadable] screens to identify new genes that influence treatment responses in vivo. We expect that our results will[unreadable] produce a better understanding of the p53 and Akt networks and how they influence drug sensitivity and[unreadable] resistance in vivo. By understanding mechanisms of drug resistance and testing strategies to circumvent it,[unreadable] we may identify new therapeutic targets or treatment strategies that can be extended to clinical trials.